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Light Acquisition

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Related Experiment Video

Updated: Sep 25, 2025

Author Spotlight: Improved Methods for Preparing Transverse Sections and Unrolled Whole Mounts of Maize Leaf Primordia for Fluorescence and Confocal Imaging

Author Spotlight: Improved Methods for Preparing Transverse Sections and Unrolled Whole Mounts of Maize Leaf Primordia for Fluorescence and Confocal Imaging

Published on: September 22, 2023

Point cloud registration method for maize plants based on conical surface fitting-ICP.

Kai'xing Zhang¹, He Chen¹, Hao Wu¹

¹College of Mechanical and Electronic Engineering, Shandong Agricultural University, Taian, 271018, China.

Scientific Reports

|April 28, 2022

Summary

This summary is machine-generated.

This study introduces an improved 3D point cloud reconstruction method for maize plants using conical surface fitting and Iterative Closest Point (ICP) registration. The new approach enhances data collection efficiency and accuracy for agricultural research.

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Last Updated: Sep 25, 2025

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Published on: October 9, 2018

Area of Science:

Agricultural Engineering
Computer Vision
3D Reconstruction

Background:

Accurate 3D models of maize plants are crucial for growth monitoring and agricultural machinery development.
Existing 3D data collection and registration methods suffer from low efficiency and poor accuracy.

Purpose of the Study:

To develop an efficient and accurate point cloud registration method for maize plants.
To improve the 3D reconstruction of maize plants for agricultural applications.

Main Methods:

Utilized an automatic platform with Kinect V2 for multi-angle point cloud collection.
Employed conical surface fitting for coarse registration and interval Iterative Closest Point (ICP) for precise registration.
Applied Delaunay triangulation for point cloud meshing.

Main Results:

Achieved full-angle registration in 57.32 seconds with a mean distance error of 1.98 mm.
Reconstructed maize plant models exhibited relative errors within 5% compared to the actual plant.
The reconstructed models are suitable for research purposes.

Conclusions:

The proposed conical surface fitting-ICP registration method significantly improves the accuracy and efficiency of 3D maize plant reconstruction.
The developed method provides a reliable tool for agricultural research and development.
The high-fidelity reconstructed models can effectively substitute physical maize plants in research settings.